"Visualizing Data Storage: This Hellabytes (Part 3)
Let's face it, time is evolving and technology is growing'¦rapidly. Technology such as the internet and social media has acted as a fan to the flame that has allowed data to grow at an exponential rate. Sites such as Facebook, Twitter and Instagram are not only doubling the amount of knowledge we are producing but are also causing us to question what's next. Digital data can be found everywhere and as technology grows it seems there is no end in sight. In fact the question that seems to be circulating the web is what should we do to prepare for this Data Boom? The White House took a step towards preparing for the Data Boom when they launched the ""Big Data"" Initiative in 2012, 6 federal departments and agencies committed to over $200 million dollars to improve tools and techniques to organize volumes of digital data. Although there are still many ways that companies, organizations and even policy makers can prepare for Big Data its always best to start with the basics.
1. Think Exponentially
First things first, to get ready for the future we must understand what we are up against. If you have followed us through parts 1 and 2 of Visualizing Data Storage hopefully you have a better understanding of the different capacities in which data can be stored. Next, we must arm ourselves with the facts of what's happening in technology today and how it can affect our data in the future. To train our brain we must focus on two words: Exponential Growth. We must at least have a basic understanding of what it means for something to grow exponentially. According to Albert Bartlett, a respected physics professor, Exponential Growth can be defined as consistent growth at a certain percentage rate each year. In his famous lecture ""Arithmetic, Population and Energy"" given in 1969, he believed that ""the greatest shortcoming of the human race is our inability to understand the exponential function"". According to the ""Knowledge Doubling Curve"" Buckminster Fuller noted that until the 1900's human knowledge doubled approximately every century. By the late 1940s human knowledge was thought to be doubling every 25 years. With today's technology, human knowledge is currently estimated to double every 13 months. This gives us our first great example of Exponential Growth. The rapid rate at which our data has grown over the years is undeniable.
To better picture this growth in terms of data; let's take a look at your relationship with Google. If they store every search you've ever made, every email you've ever received on Gmail, and also have kept a record of every chat you've ever engaged in using Google Talk- think of just how much data that would be over time? Now multiply that by every person in the world. That's a lot of data accumulated just by Google, now add in Facebook, Twitter and Instagram. The amount of data stored is almost impossible to actually imagine and the numbers are continuing to grow exponentially even as you read this very article.
2. Simplify the Growth
Once we understand data growth, the first issues to address are; How can we better organize our data? What should it be called? How can we refer to a measurement that we don't have name for? Since our widely used SI Prefix system stops at a Yottabyte we must look to scientists and researchers to come to an agreement and add to the measurement system. Many researchers argue that because we haven't reached a Yottabyte worth of data it isn't crucial that we expand the metrics system. On the other hand, there are researchers who are already preparing for the Data Boom to continue. They believe that we need to not only come up with a name for the next unit of measurement but also think of a way to simplify the scientific descriptions of storage capacity. Researchers have already begun to think of names and popular terminology ideas that include Brontobytes (named after the largest dinosaur), Geopbytes and the controversial term Hellabytes (AKA ""a hell of a lot of data""). If they can think of a one size fits all description for data storage, just as designers have in fashion, it would be a great way to simplify data measurements by converting them to just one measurement. It would be easier to understand and much more convenient. Although somewhat controversial, using terminology such as a Hellabytes might be exactly what we need to simplify our scientific data in terms of measurement. According to the Pro-Hellabyte petition circulating the web via Facebook, ""by using the measurement Hellabyte, the complexity of high-magnitude nomenclature would be greatly reduced."" The page goes on to list examples such as how the suns mass would equal 0.3 hellawatts rather than 300 yottawatts. By simplifying the terminology we are allowing for our data to be easily organized which will be crucial if it continues to grow exponentially.
3. Let Growth Motivate Change
Although this could be left to an article entirely by itself, the growth in data can open doors to many changes in the world. Instead of being fearful of technology, we can let it motivate changes in policy and education. It's hard to fear that which you are prepared for. By understanding data storage capacity and simplifying it into a means which we will all understand we would then be able to implement changes in policies such as security and educational skills needed to better handle the growth.
According to Techamerica.org, by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills. America must evolve by creating more Big Data courses to educate students on the changes in technology and teach them how to prepare for it in the work force. To help with this, the National Science Foundation (NSF) funded $10 million dollars to the University of California to research further into Big Data to learn ways of ""managing, analyzing, visualizing and extracting"" data. They also have encouraged other research universities to create graduate programs that assist in preparing the next generation of scientists and engineers.
Next policies must begin to evolve, most importantly policies that relate to security. Security initiatives must be created at larger scales that are fit to handle Big Data. Along with this, companies must hire individuals trained with the knowledge and skillset of how to optimize and organize these changes.
Albert Bartlett once said ""Much of our technology will be a million times more powerful in 20 years"". At the rate that our data is growing, we may be a million times more powerful before we know it. With each day bringing new possibilities to the field of data management, there's many ways we can get prepared. Wherever we decided to begin'¦ let's begin today."